In manufacturing products, a processing tool executes a treatment according to predetermined conditions on material to be treated. Examples are semiconductor processing tools for the treatment of semiconductor wafers, chemical reactors etc. A semiconductor processing tool typically comprises a number of devices like wafer-handling robots, valves, mass flow controllers, a temperature controller providing input signals to a thyristor pack or silicon controlled rectifier, empowering a heating element, etc. A semiconductor processing tool controller controls these devices to effectuate control over processing conditions such as gas flows, pressure, temperature, etc. For this purpose, the controller comprises a number of digital inputs and outputs and a number of analog inputs and outputs. Via the outputs, the various devices are controlled, and via the inputs, information is collected about the actual conditions in the tool.
These semiconductor processing tools are used to manufacture a myriad of semiconductor products. The consistency and quality of these semiconductor products depends on the consistency and quality of the semiconductor processing tools that are used to manufacture these products. Accordingly, when manufacturing semiconductor processing tools and when installing semiconductor processing tools in a production line, it is desirable that the tools behave consistently or match each other (i.e. “tool matching”) to assure a desired level of tool quality.
When manufacturing semiconductor processing tools, quality assurance procedures typically involve making adjustments and performing tests to measure the effect of those adjustments on the performance of the tools. When the tests are performed, certain performance variables are measured and the results are recorded. For verification, the results for the performance variables are then compared to a predefined target value within a predefined window that sets allowable tolerances for tool performance. For example, one test may involve verifying the performance of a heating element. An exemplary performance variable for the heating element is the actual voltage applied to or current through the element in response to particular control signals, which voltage or current should be within a range when the heating element is at a desired temperature. To test the heating element, predetermined signals are sent to control the power sent to the heating element and a voltage or current reading is taken. The measured quantity is compared against expected or desired values for the voltage or current in response to the same control signals. When appropriate, further adjustments may be made, followed by further measuring, recording, comparing or verifying. The process of measurement, recording, and verification is called “fingerprinting.”
In the past, quality control tests and results have been manually recorded in paper forms and/or in spreadsheet software programs, such as ones commercially available for office use. This process has disadvantages. First, the paper forms and spreadsheet software programs provided a slow and often impractical system both for analyzing the overall status of the semiconductor processing tool and for comparing that status to the tool's history of performance. Consequently, when a manufacturer of the tool spent more time spent on testing, its manufacturing costs increased and its profits decreased. Similarly, when a purchaser of the tool spent more time spent on testing, the tool's downtime increased and the purchaser's profits decreased. Second, because semiconductor processing tools are often customized according to customers' requests, the forms and/or spreadsheets had to be updated with each change in the tool configuration, which was a slow process. Third, the manual entry entails increased labor costs particularly since quality control tests are performed after a routine maintenance and disassembly to replace consumable parts. Fourth, the forms and spreadsheets risked being lost or misplaced. With the forms and/or spreadsheets, verifying a large set of performance variables (e.g., when testing most or all of the tool's subsystems) was slow, which meant longer manufacturing time for manufacturers and longer downtime for purchasers. Finally, the prior systems did not provide easy means of comparing the test results from one QC run to another QC run, the more so if the first QC run is performed by the manufacturer of the semiconductor processing tools and the other QC run is performed by purchasers of the semiconductor processing tools. Consequently, the customers found it difficult to monitor any changes in the tool.
Embodiments of the present invention seek to overcome some or all of these and other problems.